# Xiaomi-Robotics-1 Breaks the Data Barrier in Robotics The new robotics model pushes boundaries with large-scale data and training. - **Source:** [Hacker News (news.ycombinator.com)](https://brifing.si/source/13c923cd-6d99-442b-9b8b-1181f4d8cd91) - **Published:** 2026-07-20 - **Topic:** [Data & AI](https://brifing.si/c/data-ai) - **Original article:** - **On Brifing:** https://brifing.si/s/1b0da9eb-02e5-47a1-852f-d473b8522298 ## The Data Barrier in Robotics Access to large-scale, high-quality data in robotics has been a challenge, limiting the scalability of policy models. Xiaomi-Robotics-1 offers a new approach to overcome this barrier. ## Large-Scale Pre-Training Xiaomi-Robotics-1 uses 100,000 hours of embodiment-free (UMI) pre-training data. This data covers over 1,700 scenarios and is processed with automated labeling. ## Real Robot Data Post pre-training, the model is trained with real robot data. Xiaomi collected 7,200 hours of data in real homes to prepare the model for real-world tasks. ## Two-Stage Training The model learns general representations during pre-training and then aligns with real robots and natural language commands. This makes the model versatile across a wide range of tasks. ## Adaptation to New Tasks Xiaomi-Robotics-1 can efficiently learn new tasks. For example, it achieves a 75% success rate in tasks like phone packing or laundry loading. ## Simulation Success The model achieves top results in four major simulation benchmarks, proving its generalization and scalability gains. ## Sources covering this story - https://robotics.xiaomi.com/xiaomi-robotics-1.html — --- _Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._